When is an ethics course not an ethics course?

There seems to be a lot more discussion of ethics in scientific news and articles these days compared to the distant past (e.g. when I was a graduate student). This may be due to an increased complexity in the practice of science — issues like data sharing, for example, are more difficult than they used to be — or an increase in incidents of irreproducible results or actual fraud, or perhaps simple fashions about what’s worth discussing. Various funding agencies, notably the NIH and NSF, now require training in the “responsible conduct of research” (RCR) for graduate students funded by their grants. Though my research group and some of my colleagues’ have implemented ethics discussions in our group meetings, my department as a whole doesn’t have anything of this sort that all graduate students experience. (Other science departments here at Oregon do.) Thinking that this isn’t good, I (perhaps foolishly) volunteered to teach a graduate ethics workshop, which I’ll do next term together with another faculty member, in addition to our usual teaching tasks.

It’s interesting to think about what should go into such a workshop. One key thing I’ve realized is that it’s a mistake to think of the course as an “ethics workshop,” rather than a “workshop on topics in the responsible conduct of research.” Sadly, the latter is unwieldy. The former, though, causes problems, especially in communicating with colleagues. What’s the distinction, and what’s wrong with an “ethics workshop?”

First, I would argue that training in ethics per se is rather pointless. Nearly all of us know that lying, cheating, and stealing are bad, and the tiny fraction of people who don’t grasp this aren’t going to be convinced of the error of their ways by sitting in a classroom. I am reminded, in writing this, of the surreal form the university asks faculty to fill out each year about reporting grant activity and related things that essentially asks, “are you lying?” I showed this to my then-four-year old a few years ago; he recognized that the only possible answer, whether one is honest or dishonest, is “no.” (The kids and I used to discuss Knights and Knaves puzzles a lot…)

Second, the more generally applicable and interesting issues are those that aren’t as straightforward to map onto right and wrong. These are also issues that relate to the social, economic, and structural framework in which science is done. How do we handle data? How does publishing work? I’ll flesh out some examples below. In addition to being relevant to the practice of science, some knowledge about these issues at the start of one’s graduate training can help prevent conflict, frustration, or even the temptations of unethical behavior later on. Also, I’d argue, learning about the “landscape” of science is an important part of being a graduate student.

Referring to a course on RCR as an ethics course is a convenient shorthand, but I’ve learned that it causes confusion. It also, quite rightly, makes some faculty reluctant to support it, for the reasons noted two paragraphs above.

Topics

I’ve sketched several topics that would be worth discussing in this proposed RCR workshop. Here they are, with a little bit of commentary:

Data handling and management — What are our responsibilities with respect to preserving data, and also making it available to others? What do funding agencies and others say about this? What do we do, in practice, in an age of giant datasets? What distinguishes “raw data” from reduced data? This last question, by the way, is one that has provoked spirited discussion at microscopy conferences I’ve been to.

Data integrity — Can one justify throwing out “bad” data points? If so, how, or why? This is a difficult, and very common, question. It connects also to contemporary thoughts on fitting and data analysis; see e.g. this. This topic also spans the handling of images, and image manipulation.

Publishing and Authorship — How does the publication processes work, and how is it changing? What are authorship criteria and roles, and what do various professional societies say about them?

Research Misconduct and Scientific Fraud — I.e. actual ethics! We should definitely look at case studies, of which there are lots of interesting ones! Arguably the most famous in physics is the story of Jan Henrik Schön.

Statistics and ethics — A lack of understanding (or mis-understanding) of statistics, coupled with poor experimental design, underlies the present proliferation of mediocre and irreproducible studies — see e.g. this, this, or this for some snippets of the relevant discussions. This phenomenon is fascinating. But what, one might ask, does it have to do with physics, which is relatively free of the dispiriting methodology that seems to plague, for example, sociology or epidemiology? So far, not much, thankfully. But (i) similar issues come up in physics, for example in the dodgy or delusional ways physicists tend to fit power-laws to everything; and (ii) I would expect issues of statistics and perilous data-mining to become more common in physics, as datasets grow in size and complexity. OK, one replies, but what does this have to do with ethics or RCR? It occurs to me, reading a lot of examples of bad science, that the practices employed are ethical (in the sense of being with a sincere belief in their validity) only if one is ignorant of how to handle noise, uncertainty, and other quantitative aspects of data. But ignorance shouldn’t, of course, be a justification for bad science. Do we then have an ethical obligation to understand how to treat data? I haven’t seen this generally discussed, and it would be interesting to explore further. I’ll note that these ar half-formed thoughts, that may not make it into the course!

Ethical issues relating to environment, science policy, and law — (This one is from my co-teaching colleague.) What is the relationship between politically neutral science and areas of public policy that are closely connected to science (e.g. climate change)?

More things about how science is done — It’s useful to understand the landscape of science — the flows of money, people, etc. This affects graduate students quite directly, in topics like jobs, funding, etc., and it wouldn’t hurt to have some exposure to it. As I often do, I’ll note Paula Stephan’s excellent “How Economics Shapes Science” as a resource on this.

Structure

The structure of this workshop is still to be determined. The challenges are (i) to satisfy the dictates of the funding agencies, which are very vague, (ii) to make it worthwhile for students, (iii) to avoid taking up too much of research-active students’ time, and (iv) to avoid taking up too much of my time. My own preference is to have weekly 1 hour meetings, not occurring in the middle of the day, for some number of weeks between 5 and 10. Various faculty have spoken in favor of more or less time. I view the Spring launch of this workshop as an experiment — we’ll see what happens!

The workshop itself should be mostly discussion based. There are good readings on most of these topics, e.g. this available free from the National Academies.

Today’s illustration…

…is a kestrel I painted a few weeks ago, shortly after spotting both a kestrel and a bald eagle (not together) on my bike ride to work one morning. The eagle was surveying the Willamette River. The kestrel was standing in the middle of a road, devouring some smaller creature.